LINC01002 functions as a ceRNA to regulate FRMD8 by sponging miR-4324 for the development of COVID-19.

BACKGROUND: Syndrome coronavirus-2 (SARS-CoV-2) has developed various strategies to evade the antiviral impact of type I IFN. Non-structural proteins and auxiliary proteins have been extensively researched on their role in immune escape. Nevertheless, the detailed mechanisms of structural protein-induced immune evasion have not been well elucidated. METHODS: Human alveolar basal epithelial carcinoma cell line (A549) was stimulated with polyinosinic-polycytidylic acid (PIC) and independently transfected with four structural proteins expression plasmids, including nucleocapsid (N), spike (S), membrane (M) and envelope (E) proteins. By RT-qPCR and ELISA, the structural protein with the most pronounced inhibitory effects on IFN-ß induction was screened. RNA-sequencing (RNA-Seq) and two differential analysis strategies were used to obtain differentially expressed genes associated with N protein inhibition of IFN-ß induction. Based on DIANA-LncBase and StarBase databases, the interactive competitive endogenous RNA (ceRNA) network for N protein-associated genes was constructed. By combining single-cell sequencing data (GSE158055), lncRNA-miRNA-mRNA axis was further determined. Finally, RT-qPCR was utilized to illustrate the regulatory functions among components of the ceRNA axis. RESULTS: SARS-CoV-2 N protein inhibited IFN-ß induction in human alveolar epithelial cells most significantly compared with other structural proteins. RNA-Seq data analysis revealed genes related to N protein inhibiting IFNs induction. The obtained 858 differentially expressed genes formed the reliable ceRNA network. The function of LINC01002-miR-4324-FRMD8 axis in the IFN-dominated immune evasion was further demonstrated through integrating single-cell sequencing data. Moreover, we validated that N protein could reverse the effect of PIC on LINC01002, FRMD8 and miR-4324 expression, and subsequently on IFN-ß expression level. And LINC01002 could regulate the production of FRMD8 by inhibiting miR-4324. CONCLUSION: SARS-CoV-2 N protein suppressed the induction of IFN-ß by regulating LINC01002 which was as a ceRNA, sponging miR-4324 and participating in the regulation of FRMD8 mRNA. Our discovery provides new insights into early intervention therapy and drug development on SARS-CoV-2 infection.

Systematic Evaluation of Ultrasonic In-Line Inspection Techniques for Oil and Gas Pipeline Defects Based on Bibliometric Analysis.

The global reliance on oil and gas pipelines for energy transportation is increasing. As the pioneering review in the field of ultrasonic defect detection for oil and gas pipelines based on bibliometric methods, this study employs visual analysis to identify the most influential countries, academic institutions, and journals in this domain. Through cluster analysis, it determines the primary trends, research hotspots, and future directions in this critical field. Starting from the current global industrial ultrasonic in-line inspection (ILI) detection level, this paper provides a flowchart for selecting detection methods and a table for defect comparison, detailing the comparative performance limits of different detection devices. It offers a comprehensive perspective on the latest ultrasonic pipeline detection technology from laboratory experiments to industrial practice.

Assessment of aortic hemodynamics in patients with thoracoabdominal aortic aneurysm using four-dimensional magnetic resonance imaging: a cross-sectional study.

Background: Thoracoabdominal aortic aneurysms (TAAAs) are rare but complicated aortic pathologies that can result in high morbidity and mortality. The whole-aorta hemodynamic characteristics of TAAA survivors remains unknown. This study sought to obtain a comprehensive view of flow hemodynamics of the whole aorta in patients with TAAA using four-dimensional flow (4D flow) magnetic resonance imaging (MRI). Methods: This study included patients who had experienced TAAA or abdominal aortic aneurysm (AAA) and age- and sex-matched volunteers who had attended China Hospital from December 2021 to December 2022 in West. Patients with unstable ruptured aneurysm or other cardiovascular diseases were excluded. 4D-flow MRI that covered the whole aorta was acquired. Both planar parameters [(regurgitation fraction (RF), peak systolic velocity (Vmax), overall wall shear stress (WSS)] and segmental parameters [pulse wave velocity (PWV) and viscous energy loss (VEL)] were generated during postprocessing. The Student's t-test or Mann-Whitney test was used to compare flow dynamics among the three groups. Results: A total of 11 patients with TAAA (mean age 53.2±11.9 years; 10 males), 19 patients with AAA (mean age 58.0±11.7 years; 16 males), and 21 controls (mean age 55.4±15.0 years; 19 males) were analyzed. The patients with TAAA demonstrated a significantly higher RF and lower Vmax in the aortic arch compared to healthy controls. The whole length of the aorta in patients with TAAA was characterized by lower WSS, predominantly in the planes of pulmonary artery bifurcation and the middle infrarenal planes (all P values <0.001). As for segmental hemodynamics, compared to controls, patients with TAAA had a significantly higher PWV in the thoracic aorta (TAAA: median 11.41 m/s, IQR 9.56-14.32 m/s; control: median 7.21 m/s, IQR 5.57-7.79 m/s; P<0.001) as did those with AAA (AAA: median 8.75 m/s, IQR 7.35-10.75 m/s; control: median 7.21 m/s, IQR 5.57-7.79 m/s; P=0.024). Moreover, a greater VEL was observed in the whole aorta and abdominal aorta in patients with TAAA. Conclusions: Patients with TAAA exhibited a stiffer aortic wall with a lower WSS and a greater VEL for the whole aorta, which was accompanied by a higher RF and lower peak velocity in the dilated portion of the aorta.

A comprehensive multi-omics analysis identifies a robust scoring system for cancer-associated fibroblasts and intervention targets in colorectal cancer.

BACKGROUND: Cancer-associated fibroblasts (CAF) play a critical role in promoting tumor growth, metastasis, and immune evasion. While numerous studies have investigated CAF, there remains a paucity of research on their clinical application in colorectal cancer (CRC). METHODS: In this study, we collected differentially expressed genes between CAF and normal fibroblasts (NF) from previous CRC studies, and utilized machine learning analysis to differentiate two distinct subtypes of CAF in CRC. To enable practical application, a CAF-related genes (CAFGs) scoring system was developed based on multivariate Cox regression. We then conducted functional enrichment analysis, Kaplan-Meier plot, consensus molecular subtypes (CMS) classification, and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm to investigate the relationship between the CAFGs scoring system and various biological mechanisms, prognostic value, tumor microenvironment, and response to immune checkpoint blockade (ICB) therapy. Moreover, single-cell transcriptomics and proteomics analyses have been employed to validate the significance of scoring system-related molecules in the identity and function of CAF. RESULTS: We unveiled significant distinctions in tumor immune status and prognosis not only between the CAF clusters, but also across high and low CAFGs groups. Specifically, patients in CAF cluster 2 or with high CAFGs scores exhibited higher CAF markers and were enriched for CAF-related biological pathways such as epithelial-mesenchymal transition (EMT) and angiogenesis. In addition, CAFGs score was identified as a risk index and correlated with poor overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and recurrence-free survival (RFS). High CAFGs scores were observed in patients with advanced stages, CMS4, as well as lymphatic invasion. Furthermore, elevated CAFG scores in patients signified a suppressive tumor microenvironment characterized by the upregulation of programmed death-ligand 1 (PD-L1), T-cell dysfunction, exclusion, and TIDE score. And high CAFGs scores can differentiate patients with lower response rates and poor prognosis under ICB therapy. Notably, single-cell transcriptomics and proteomics analyses identified several molecules related to CAF identity and function, such as FSTL1, IGFBP7, and FBN1. CONCLUSION: We constructed a robust CAFGs score system with clinical significance using multiple CRC cohorts. In addition, we identified several molecules related to CAF identity and function that could be potential intervention targets for CRC patients.

Deep Learning Image Reconstruction for Transcatheter Aortic Valve Implantation Planning: Image Quality, Diagnostic Performance, Contrast volume and Radiation Dose Assessment.

RATIONALE AND OBJECTIVES: To assess image quality, contrast volume and radiation dose reduction potential and diagnostic performance with the use of high-strength deep learning image reconstruction (DLIR-H) in transcatheter aortic valve implantation (TAVI) planning CT. METHODS: We prospectively enrolled 128 patients referred to TAVI-planning CT. Patients were randomly divided into two groups: DLIR-H group (n = 64) and conventional group (n = 64). The DLIR-H group was scanned with tube voltage of 80kVp and body weighted-dependent contrast injection rate of 28mgI/kg/s, images reconstructed using DLIR-H; the conventional group was scanned with 100kVp and contrast injection rate of 40mgI/kg/s, and images reconstructed using adaptive statistical iterative reconstruction-V at 50% (ASIR-V 50%). Radiation dose, contrast volume, contrast injection rate, and image quality were compared between the two groups. The diagnostic performance of TAVI planning CT for coronary stenosis in 115 patients were calculated using invasive coronary angiography as golden standard. RESULTS: DLIR-H group significantly reduced radiation dose (4.94 ± 0.39mSv vs. 7.93 ± 1.20mSv, p < 0.001), contrast dose (45.28 ± 5.38 mL vs. 63.26 ± 9.88 mL, p < 0.001), and contrast injection rate (3.1 ± 0.31 mL/s vs. 4.9 ± 0.2 mL/s, p < 0.001) compared to the conventional group. Images in DLIR-H group had significantly higher SNR and CNR (all p < 0.001). For the diagnostic performance on a per-patient basis, TAVI planning CT in the DLIR-H group provided 100% sensitivity, 92.1% specificity, 100% negative predictive value (NPV), and 84.2% positive predictive value for the detection of > 50% stenosis. In the conventional group, the corresponding results were 94.7%, 95.3%, 97.6%, and 90.0%, respectively. CONCLUSION: DLIR-H in TAVI-planning CT provides improved image quality with reduced radiation and contrast doses, and enables satisfactory diagnostic performance for coronary arteries stenosis.

Imaging-based deep learning in kidney diseases: recent progress and future prospects.

Kidney diseases result from various causes, which can generally be divided into neoplastic and non-neoplastic diseases. Deep learning based on medical imaging is an established methodology for further data mining and an evolving field of expertise, which provides the possibility for precise management of kidney diseases. Recently, imaging-based deep learning has been widely applied to many clinical scenarios of kidney diseases including organ segmentation, lesion detection, differential diagnosis, surgical planning, and prognosis prediction, which can provide support for disease diagnosis and management. In this review, we will introduce the basic methodology of imaging-based deep learning and its recent clinical applications in neoplastic and non-neoplastic kidney diseases. Additionally, we further discuss its current challenges and future prospects and conclude that achieving data balance, addressing heterogeneity, and managing data size remain challenges for imaging-based deep learning. Meanwhile, the interpretability of algorithms, ethical risks, and barriers of bias assessment are also issues that require consideration in future development. We hope to provide urologists, nephrologists, and radiologists with clear ideas about imaging-based deep learning and reveal its great potential in clinical practice.Critical relevance statement The wide clinical applications of imaging-based deep learning in kidney diseases can help doctors to diagnose, treat, and manage patients with neoplastic or non-neoplastic renal diseases.Key points• Imaging-based deep learning is widely applied to neoplastic and non-neoplastic renal diseases.• Imaging-based deep learning improves the accuracy of the delineation, diagnosis, and evaluation of kidney diseases.• The small dataset, various lesion sizes, and so on are still challenges for deep learning.

hsa_circ_0002980 prevents proliferation, migration, invasion, and epithelial-mesenchymal transition of liver cancer cells through microRNA-1303/cell adhesion molecule 2 axis.

BACKGROUND: Liver cancer (LC) is a rare malignancy. Circular RNA (circRNA) dysregulation is associated with LC metastasis. hsa_circ_0002980 was found to be unexpectedly downregulated in LC tissues; however, its specific function remains unclear. METHODS: hsa_circ_0002980 expression was confirmed using RT-qPCR. The effects of circ_0002980 on the proliferation, metastasis, and EMT-related proteins of LC cells were assessed using clone formation, flow cytometry, Transwell assays, and Western blotting. The relationship between circ_0002980 and miR-1303 or miR-1303 and CADM2 was analyzed using a dual-luciferase reporter assay. Thereafter, the influence of these three genes on LC cell progression was determined through rescue experiments. RESULTS: hsa_circ_0002980 expression was lower in LC. circ_0002980 overexpression inhibited the proliferation, migration, invasion, and EMT of LC cells. In addition, circ_0002980 specifically binds to miR-1303, and the accelerated effect of miR-1303 overexpression on LC progression was partially reversed by circ_0002980. Moreover, miR-1303 can also target CADM2, and CADM2-mediated prevention can also be attenuated by miR-1303 overexpression. CONCLUSIONS: In LC cells, circ_0002980 upregulation prevents cell proliferation, metastasis, and EMT by affecting the miR-1303/CADM2 axis. Therefore, this axis may be a novel therapeutic target in LC.

Generation of induced pluripotent stem cell line (TMOi001-A-11) carrying a homozygous deletion in the synemin gene using CRISPR/Cas9.

A number of genetic variants in the SYNM gene encoding for the intermediate filament synemin have been reported in patients with cardiomyopathies, skeletal myopathies, cancer and certain neurodegenerative disorders. To better understand its role, we generated a human induced pluripotent stem cell line with a homozygous deletion in the SYNM gene by CRISPR/Cas9 genome editing. The synemin-knockout human induced pluripotent stem cells exhibit typical morphology of pluripotent cells, expression of pluripotency markers, normal karyotype and differentiation capacity in the three germ layers. This line will allow us to investigate the role of synemin in cardiomyopathy upon differentiation into beating cardiomyocytes.

SUV39H1 is a novel biomarker targeting oxidative phosphorylation in hepatitis B virus-associated hepatocellular carcinoma.

BACKGROUND: As a histone methyltransferase, suppressor of variegation 3-9 homolog 1 (SUV39H1) plays an important role in the occurrence and development of cancer. To explore the mechanism and biological function of SUV39H1 in hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) can gain an insight into the pathogenesis of HBV-HCC. METHODS: The effect of HBV infection on SUV39H1 in hepatoma cells was detected. CCK-8, colony growth assay and wound healing assay were used to assess the proliferation and migration of HBV-positive hepatoma cells. RNA sequencing (RNA-seq) was applied to find differential genes and enriched pathways. The serum SUV39H1 level in HBV-HCC patients was detected and its correlation with clinical indicators was analyzed. RESULTS: SUV39H1 was increased by HBV infection and promoted the proliferation and migration of hepatoma cells. SUV39H1 could upregulate the expression of mitochondrial oxidative phosphorylation (OXPHOS) pathway-related genes. OXPHOS pathway inhibitors could reduce the capacity of proliferation and migration of hepatoma cells after overexpressing SUV39H1. Serum SUV39H1 levels were higher in chronic hepatitis B (CHB) patients than in healthy controls and higher in HBV-HCC patients than in CHB patients. In the diagnosis of HCC, the predictive value of SUV39H1 combined with alpha-fetoprotein (AFP) was better than that of AFP alone. CONCLUSION: SUV39H1 is regulated by HBV infection and promotes the proliferation and migration of hepatoma cells by targeting OXPHOS pathway. It indicates that SUV39H1 may be a new biomarker of the diagnosis of HCC.

Dual-layer spectral computed tomography aortography using a seventy-five-percent-reduced iodine dose protocol and multiparameter spectral imaging: comparison with conventional computed tomography imaging.

Background: Computed tomography angiography (CTA) is the recommended diagnostic and follow-up imaging modality for acute aortic dissection (AD). However, the high-contrast medium burden associated with repeated CT aortography follow-ups remains a significant concern. This prospective study aimed to assess whether an ultra-low contrast dose (75% cutoff) aortic CTA protocol on dual-layer spectral CT could achieve comparable image quality with the full dose protocol. We also investigated the image quality of the virtual noncontrast (VNC) images derived from the ultra-low dose protocol. Methods: This study included 37 consecutive patients who were referred to aortic CTA from May 2022 to August 2022. The enrolled patients underwent full-dose contrast CTA and ultra-low dose (reduced to 25% of conventional) contrast CTA on dual-layer spectral CT in 1 day. Virtual monochromatic images (VMIs) were reconstructed with 40 and 70 keV. The VNC images were reconstructed for both protocols. Objective image quality evaluation, recorded as signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs), was compared between the groups using 1-way analysis of variance and post hoc analysis with Bonferroni correction. Subjective image quality was also compared between the groups. Finally, VNC images derived from the low-dose (VNClow) and full-dose (VNCfull) protocols were compared to the true noncontrast (TNC) images. Results: Neither CNR nor SNR was lower for the 40-keV images reconstructed from the ultra-low dose group compared to the conventional images. Both were significantly higher than those of the 70-keV images. Regarding subjective image quality, vessel enhancement was not significantly different between the 40-keV VMI and full-dose images [ascending aorta (AAO): 4.37±0.46 vs. 4.57±0.48, P=0.096; brachiocephalic arteries: 4.34±0.45 vs. 4.51±0.49, P=0.152; abdominal aortic side branch: 4.42±0.48 vs. 4.51±0.49, P=0.480]. The VNClow images were similar to the TNC images but significantly different from the VNCfull images (P<0.001). Conclusions: Ultra-low contrast aortic CTA with a 75%-reduced iodine dose using dual-layer spectral CT and the derived VNC achieved image quality comparable to that of conventional CTA and TNC images.

Research on the biological mechanism and potential application of CEMIP.

Cell migration-inducing protein (CEMIP), also known as KIAA1199 and hyaluronan-binding protein involved in hyaluronan depolymerization, is a new member of the hyaluronidase family that degrades hyaluronic acid (HA) and remodels the extracellular matrix. In recent years, some studies have reported that CEMIP can promote the proliferation, invasion, and adhesion of various tumor cells and can play an important role in bacterial infection and arthritis. This review focuses on the pathological mechanism of CEMIP in a variety of diseases and expounds the function of CEMIP from the aspects of inhibiting cell apoptosis, promoting HA degradation, inducing inflammatory responses and related phosphorylation, adjusting cellular microenvironment, and regulating tissue fibrosis. The diagnosis and treatment strategies targeting CEMIP are also summarized. The various functions of CEMIP show its great potential application value.

Carbonation of steel slag at low CO2 concentrations: Novel biochar cold-bonded steel slag artificial aggregates.

Carbonation technology resolves the volume expansion of steel slag by combining CO2 with f-CaO, but the previous stringent carbonation conditions (99%vol) significantly limit the application prospect of steel slag. To achieve the carbonation of steel slag at lower CO2 concentrations, a novel cold-bonded artificial aggregates (CASSAs) based on steel slag and biochar is produced in this paper. The carbon capture capacities of CASSAs with different biochar contents (5 wt%, 10 wt%, and 15 wt%) are investigated in a low-CO2 concentration environment (10.79 % vol) and natural environment using the porosity and CO2 adsorption capacity of biochar. The changes in the performance of CASSAs before and after carbonation are investigated at different curing ages (7 d and 28 d). The results reveal that biochar increases the pores of the CASSAs. At 7 d, B15 achieves complete carbonation at low concentrations and can uptake 6.5 wt% of CO2. CO2 adsorption capacity by biochar in the natural environment facilitates the diffusion of CO2 in CASSAs. Regarding mechanical properties, the addition of biochar makes B15 at 7 d half as strong as B0, but B15 exhibits long-term strength development. B15 at 7 d has a strength of 8.49 MPa after carbonation, which is almost the same as B0. In addition, B15 achieves a net CO2 emission of -39.9 kg/ton. This study combines biochar with CASSAs to provide a potential method to carbonate steel slag at low CO2 concentrations. A new methodology was also used to quantitatively assess the ability of biochar CASSAs to solidify CO2 under low concentration conditions and natural environments from a macroscopic perspective. Biochar CASSAs have great potential to realize resource utilization and carbon capture from steel slag.

Synthesis of geopolymer using municipal solid waste incineration fly ash and steel slag: Hydration properties and immobilization of heavy metals.

In this study, a novel method for the disposal of municipal solid waste incineration fly ash (MSWIFA) was proposed. By applying geopolymer technology, steel slag (SS) and MSWIFA were used together as precursors to synthesize a cementitious material with sufficient strength that is useable in construction. The effects of the dosages of SS and alkaline activator on the properties of the geopolymer were investigated. Compressive testing was used to characterize the mechanical properties of the geopolymer. X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) were used for microscopic analysis. Leaching tests were performed to assess the immobilization effect of the geopolymer on heavy metals. The results showed that the compressive strength of the geopolymer reached 23.03 MPa at 56 d with 20% SS and 11% Na2O admixture. Highly polymerized hydration products, such as C-(A)-S-H gels and N-A-S-H gels, contributed to the compact microstructure, which provided mechanical strength and limited the migration and leaching of heavy metals in the geopolymer matrix. In terms of the results, this work is significant for the development of MSWIFA management.

MRI-based multiregional radiomics for preoperative prediction of tumor deposit and prognosis in resectable rectal cancer: a bicenter study.

OBJECTIVE: To build T2WI-based multiregional radiomics for predicting tumor deposit (TD) and prognosis in patients with resectable rectal cancer. MATERIALS AND METHODS: A total of 208 patients with pathologically confirmed rectal cancer from two hospitals were prospectively enrolled. Intra- and peritumoral features were extracted separately from T2WI images and the least absolute shrinkage and selection operator was used to screen the most valuable radiomics features. Clinical-radiomics nomogram was developed by radiomics signatures and the most predictive clinical parameters. Prognostic model for 3-year recurrence-free survival (RFS) was constructed using univariate and multivariate Cox analysis. RESULTS: For TD, the area under the receiver operating characteristic curve (AUC) for intratumoral radiomics model was 0.956, 0.823, and 0.860 in the training cohort, test cohort, and external validation cohort, respectively. AUC for the peritumoral radiomics model was 0.929, 0.906, and 0.773 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for combined intra- and peritumoral radiomics model was 0.976, 0.918, and 0.874 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for clinical-radiomics nomogram was 0.989, 0.777, and 0.870 in the training cohort, test cohort, and external validation cohort, respectively. The prognostic model constructed by combining intra- and peritumoral radiomics signature score (radscore)-based TD and MRI-reported lymph nodes metastasis (LNM) indicated good performance for predicting 3-year RFS, with AUC of 0.824, 0.865, and 0.738 in the training cohort, test cohort and external validation cohort, respectively. CONCLUSION: Combined intra- and peritumoral radiomics model showed good performance for predicting TD. Combining intra- and peritumoral radscore-based TD and MRI-reported LNM indicated the recurrence risk. CLINICAL RELEVANCE STATEMENT: Combined intra- and peritumoral radiomics model could help accurately predict tumor deposits. Combining this predictive model-based tumor deposits with MRI-reported lymph node metastasis was associated with relapse risk of rectal cancer after surgery. KEY POINTS: • Combined intra- and peritumoral radiomics model provided better diagnostic performance than that of intratumoral and peritumoral radiomics model alone for predicting TD in rectal cancer. • The predictive performance of the clinical-radiomics nomogram was not improved compared with the combined intra- and peritumoral radiomics model for predicting TD. • The prognostic model constructed by combining intra- and peritumoral radscore-based TD and MRI-reported LNM showed good performance for assessing 3-year RFS.

Cross-modality image translation: CT image synthesis of MR brain images using multi generative network with perceptual supervision.

BACKGROUND: Computed tomography (CT) and magnetic resonance imaging (MRI) are the mainstream imaging technologies for clinical practice. CT imaging can reveal high-quality anatomical and physiopathological structures, especially bone tissue, for clinical diagnosis. MRI provides high resolution in soft tissue and is sensitive to lesions. CT combined with MRI diagnosis has become a regular image-guided radiation treatment plan. METHODS: In this paper, to reduce the dose of radiation exposure in CT examinations and ameliorate the limitations of traditional virtual imaging technologies, we propose a Generative MRI-to-CT transformation method with structural perceptual supervision. Even though structural reconstruction is structurally misaligned in the MRI-CT dataset registration, our proposed method can better align structural information of synthetic CT (sCT) images to input MRI images while simulating the modality of CT in the MRI-to-CT cross-modality transformation. RESULTS: We retrieved a total of 3416 brain MRI-CT paired images as the train/test dataset, including 1366 train images of 10 patients and 2050 test images of 15 patients. Several methods (the baseline methods and the proposed method) were evaluated by the HU difference map, HU distribution, and various similarity metrics, including the mean absolute error (MAE), structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and normalized cross-correlation (NCC). In our quantitative experimental results, the proposed method achieves the lowest MAE mean of 0.147, highest PSNR mean of 19.27, and NCC mean of 0.431 in the overall CT test dataset. CONCLUSIONS: In conclusion, both qualitative and quantitative results of synthetic CT validate that the proposed method can preserve higher similarity of structural information of the bone tissue of target CT than the baseline methods. Furthermore, the proposed method provides better HU intensity reconstruction for simulating the distribution of the CT modality. The experimental estimation indicates that the proposed method is worth further investigation.

Reducing both radiation and contrast doses for overweight patients in coronary CT angiography with 80-kVp and deep learning image reconstruction.

PURPOSE: To investigate the use of an 80-kVp tube voltage combined with a deep learning image reconstruction (DLIR) algorithm in coronary CT angiography (CCTA) for overweight patients to reduce radiation and contrast doses in comparison with the 120-kVp protocol and adaptive statistical iterative reconstruction (ASIR-V). METHODS: One hundred consecutive CCTA patients were prospectively enrolled and randomly divided into a low-dose group (n = 50) with 80-kVp, smart mA for noise index (NI) of 36 HU, contrast dose rate of 18 mgI/kg/s and DLIR and 60 % ASIR-V and a standard-dose group (n = 50) with 120-kVp, smart mA for NI of 25 HU, contrast dose rate of 32 mgI/kg/s and 60 % ASIR-V. The radiation and contrast dose, subjective image quality score, attenuation values, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared. RESULTS: The low-dose group achieved a significant reduction in the effective radiation dose (1.01 ± 0.45 mSv vs 1.85 ± 0.40 mSv, P < 0.001) and contrast dose (33.69 ± 3.87 mL vs 59.11 ± 5.60 mL, P < 0.001) compared to the standard-dose group. The low-dose group with DLIR presented similar enhancement but lower noise, higher SNR and CNR and higher subjective quality scores than the standard-dose group. Moreover, the same patient comparison in the low-dose group between different reconstructions showed that DLIR images had slightly and consistently higher CT values in small vessels, indicating better defined vessels, much lower image noise, higher SNR and CNR and higher subjective quality scores than ASIR-V images (all P < 0.001). CONCLUSIONS: The application of 80-kVp and DLIR allows for significant radiation and dose reduction while further improving image quality in CCTA for overweight patients.

A hepatocyte-targeting nanoparticle for enhanced hepatobiliary magnetic resonance imaging.

Hepatobiliary magnetic resonance imaging (MRI) can inform the diagnosis of liver tumours in patients with liver cirrhosis and hepatitis. However, its clinical utility has been hampered by the lack of sensitive and specific contrast agents, partly because hepatocyte-specific nanoparticles, regardless of their surface ligands, are readily sequestered by Kupffer cells. Here we show, in rabbits, pigs and macaques, that the performance of hepatobiliary MRI can be enhanced by an ultrasmall nanoparticle composed of a manganese ferrite core (3 nm in diameter) and poly(ethylene glycol)-ethoxy-benzyl surface ligands binding to hepatocyte-specific transmembrane metal and anion transporters. The nanoparticle facilitated faster, more sensitive and higher-resolution hepatobiliary MRI than the clinically used contrast agent gadoxetate disodium, a substantial enhancement in the detection rate (92% versus 48%) of early-stage liver tumours in rabbits, and a more accurate assessment of biliary obstruction in macaques. The nanoparticle's performance and biocompatibility support the further translational development of liver-specific MRI contrast agents.

Using arterial phase hyperenhancement on CT instead of gadoxetic acid arterial phase enhancement may improve the diagnostic performance for hepatocellular carcinoma.

Background: The diagnostic performance for hepatocellular carcinoma (HCC) is hampered using gadoxetic acid-enhanced magnetic resonance (MR) imaging due to the high incidence of transient severe motion in arterial phase (AP). Dynamic contrast enhanced computed tomography (CT) imaging yield high detection rate for hepatic nodules in AP, and the combined use of CT arterial phase (CTAP) imaging with gadoxetic acid-enhanced MR imaging may improve the diagnostic performance for HCC. Thus, this study aimed to determine whether the combined use of CTAP and gadoxetic acid-enhanced MR imaging can improve the diagnostic performance for HCC based on various imaging diagnostic criteria. Methods: A total of 169 surgically histologically confirmed hepatic nodules (137 HCCs and 32 non-HCC-nodules) were retrospectively enrolled. Two different imaging protocol sets were reviewed: (I) full gadoxetic acid-enhanced magnetic resonance imaging (MRI) sequences; and (II) CTAP imaging combined with the gadoxetic acid-enhanced MRI but excluding the MR imaging AP images. Three independent reviewers followed the 2018 Liver Reporting and Data System (LI-RADS), European Association for the Study of the Liver (EASL), and 2018 Korean guidelines to characterize these heaptic nodules by reviewing the two imaging protocol sets and the diagnostic peformance were compared by using McNemar test. Results: The detection rate of AP hyperenhancement (APHE) was higher in CTAP than in the MR arterial phase (MRAP) for hepatic nodules (87.57% vs. 75.15%) and HCCs (97.08% vs. 82.48%) (all P<0.001). For the LI-RADS criteria, the Protocol-II increased the sensitivity to 75.91% from 70.80% of Protocol-I (P=0.016), with a minimal decrease of the specificity to 71.88% from 75.00% (P=1.000). For the EASL criteria, the numerical increases were found of Protocol-II than Protocol-I in both sensitivity (81.02% vs. 78.10%) and specificity (75.00% vs.71.88%), but with no statistical significance. For the Korean criteria, the Protocol-II increased the sensitivity to 94.89% from 83.21% of Protocol-I (P<0.001). The specificity increased to 65.63% from 62.50%, with no statistical significance (P=1.000). Conclusions: Using CTAP instead of gadoxetic acid-enhanced MRAP can improve the diagnostic sensitivity for HCC and also yields a comparable specificity. Thus, the combined use of CTAP and gadoxetic acid-enhanced MR imaging may improve the diagnostic performance for HCC.

CXCL8, CXCL9, CXCL10, and CXCL11 as biomarkers of liver injury caused by chronic hepatitis B.

Background: Chronic hepatitis B (CHB) remains a significant global health problem, leading to recurrent inflammation and liver-damaging diseases such as fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Currently, although diagnostic markers for CHB are well established, the indicators for predicting liver injury caused by hepatitis B virus (HBV) infection still need to be further explored. Thus, the identification of credible infectious indicators is urgently needed to facilitate timely clinical intervention and avoid the progression of disease malignancy. Methods: The Gene Expression Omnibus (GEO) database GSE83148 data set was used to explore the hub genes for HBV infection. The quantitative real-time polymerase chain reaction (qPCR) was used to identify the impact of HBV infection on the expression of hub gene at the cell level. At the same time, serum samples and clinical information were collected from healthy, HBV-free and CHB patients. The enzyme-linked immunosorbent assay (ELISA) was used to verify the results of cell experiments and Pearson correlation analysis was used to clarify hub genes correlation with HBV infection indicators and liver injury-related indicators. Finally, the Gene Expression Profiling Interactive Analysis (GEPIA) database was used to analyze the differences in the expression of hub gene in liver injury diseases. Results: Chemokine (C-X-C motif) ligand (CXCL)8, CXCL9, CXCL10, and CXCL11 were identified as hub genes in HBV infection. After HBV infection, the expression of the four chemokines was significantly increased and the concentrations secreted into serum were also increased. Moreover, the four chemokines were significantly correlated with HBV infection-related indicators and liver injury-related indicators, which were positively correlated with alanine aminotransferase (ALT), aspartate aminotransferase (AST) and hepatitis B e antigen (HBeAg), and negatively correlated with AST/ALT ratio and hepatitis B core antibody (HBcAb). In addition, the expression of CXCL9, CXCL10, and CXCL11 in HCC tissues was significantly higher than in normal tissues. Conclusion: Using a combination of bioinformatics, cell experiments, and clinical correlation analysis, this study showed that CXCL8, CXCL9, CXCL10, and CXCL11 can be used as serum biomarkers to forecast liver injury caused by HBV infection.

miR-301a Deficiency Attenuates the Macrophage Migration and Phagocytosis through YY1/CXCR4 Pathway.

(1) Background: the miR-301a is well known involving the proliferation and migration of tumor cells. However, the role of miR-301a in the migration and phagocytosis of macrophages is still unclear. (2) Methods: sciatic nerve injury, liver injury models, as well as primary macrophage cultures were prepared from the miR-301a knockout (KO) and wild type (WT) mice to assess the macrophage's migration and phagocytosis capabilities. Targetscan database analysis, Western blotting, siRNA transfection, and CXCR4 inhibition or activation were performed to reveal miR301a's potential mechanism. (3) Results: the macrophage's migration and phagocytosis were significantly attenuated by the miR-301a KO both in vivo and in vitro. MiR-301a can target Yin-Yang 1 (YY1), and miR-301a KO resulted in YY1 up-regulation and CXCR4 (YY1's down-stream molecule) down-regulation. siYY1 increased the expression of CXCR4 and enhanced migration and phagocytosis in KO macrophages. Meanwhile, a CXCR4 inhibitor or agonist could attenuate or accelerate, respectively, the macrophage migration and phagocytosis. (4) Conclusions: current findings indicated that miR-301a plays important roles in a macrophage's capabilities of migration and phagocytosis through the YY1/CXCR4 pathway. Hence, miR-301a might be a promising therapeutic candidate for inflammatory diseases by adjusting macrophage bio-functions.